3D neurological image retrieval with localized patholo-gycentric CMRGLC patterns

Weidong Cai*, Sidong Liu, Lingfeng Wen, Stefan Eberl, Michael J. Fulham, Dagan Feng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

33 Citations (Scopus)

Abstract

Functional neuroimaging has an important role in non-invasive diagnosis of neurodegenerative disorders. There are now large volumes of imaging data generated by functional imaging technologies and so there is a need to efficiently manage and retrieve these data. In this paper, we propose a new scheme for efficient 3D content-based neurological image retrieval. 3D pathology-centric masks were adaptively designed and applied for extracting CMRGlc (cerebral metabolic rate of glucose consumption) texture features with volumetric co-occurrence matrices from neurological FDG PET images. Our results, using 93 clinical dementia studies, show that our approach offers a robust and efficient retrieval mechanism for relevant clinical cases and provides advantages in image data analysis and management.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3201-3204
Number of pages4
ISBN (Electronic)9781424479931
ISBN (Print)9781424479948
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period26/09/1029/09/10

Keywords

  • 3D neurological image
  • Brain PET image
  • Dementia
  • Image retrieval
  • Localized retrieval

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  • Cite this

    Cai, W., Liu, S., Wen, L., Eberl, S., Fulham, M. J., & Feng, D. (2010). 3D neurological image retrieval with localized patholo-gycentric CMRGLC patterns. In 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings (pp. 3201-3204). [5651869] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIP.2010.5651869